Earticle

In keeping with the development of wireless networking technology, P2P computing is moving towards the environment of P2P based networks among mobile devices. Particularly, media streaming services using P2P have become essential technology to increase users' utilization and enhance efficiency through being grafted onto other wireless networking technologies. However, resource utilization should be enhanced, given frequent churning and delay state caused by the characteristics of mobile devices; and overall system performance should be improved through continuous contribution. Hence, this paper proposes an efficient peer allocation mechanism, in which a newly joining peer selects a proper bandwidth and a parent node having much remaining download time. Mobile P2P streaming to which this proposed technique was applied shows system improvement through continuous connection.

According to the characteristics of hyperspectral images, a novel compression and reconstruction algorithm for hyperspectal images based on compressed sensing is proposed. The random measurements of each image and the linear prediction coefficients are made at the encoder, and then transmitted sequentially to the decoder. At the decoder, in terms of apparent correlations between the adjacent spectral bands, a de-correlation algorithm based on block linear prediction model is used in reconstruction process. The inter-band redundancies are removed from the measurements of current image, thus the de-correlation image data is sparser, which can be reconstructed easily. Experimental results show that the proposed algorithm achieves improved reconstruction performance and efficiently reduces the cost of computation at the encoder, which is more suitable for hardware implementation.

Low energy consumption has always been the most important main issue in wireless sensor networks. But many applications requiring low latency and high throughput have been emerged recently. Many existing duty-cycle MAC protocols such as S-MAC [1] and T-MAC [2] provide good power efficiency but introduce significant end-to-end delay. In this paper, we proposed an energy and delay efficient duty-cycle MAC protocol which reduces data transmission delay from source node to destination node and node energy consumption in multi-hop Wireless Sensor Networks. The main goal is to design a MAC protocol for object tracking application, in which large amounts of data need to be transmitted when an event occurs. An operation cycle of the proposed MAC protocol is consists of four periods as in LO-MAC [10]. But in the proposed MAC protocol all the nodes in the data path repeat the Sleep periods only when an event occurs. And during Data period nodes immediately go into sleep mode with overhearing the PION packet. Performance evaluation shows that the proposed MAC protocol improves the transmission delay and the throughput compared to the RMAC.

While the cloud computing benefits healthcare IT modernization, it introduces new challenges for data integration, which is crucial for information sharing, data mining and business intelligence applications. Data virtualization brings a new strategy and related technologies to cope with these challenges, particularly suitable for cloud data services and SaaS (Software-as-a-Service) applications. The paper discussed a unique architecture and related technologies to implement the data virtualization for cloud data. The paper also demonstrated how this technology can be used in the real-world applications, and a city-wide healthcare appointment system has been implemented for example.

In the modern IT industrial cluster environment, IT cluster companies increasingly depend on external sources of information to promote innovation and improve their performance. In doing so, IT cluster companies should first enhance their absorptive capacities to increase their abilities to evaluate, assimilate, and apply external knowledge to their industries. Absorptive capacity is what enables companies to effectively acquire and utilize external as well as internal knowledge, which affects the company's ability to innovate and adapt to its changing environment. However, no prior studies have explored the influences of external and internal factors on the absorptive capacities and innovation performance of IT clusters. Therefore, we have demonstrated the relationship between IT cluster characteristics and the innovation performance of firms located in those clusters through an empirical investigation of IT firms based in the Teheran, Guro, and Daedeok Valleys, which are South Korea’s three major IT clusters. This study developed a research model to explain the effects of IT industrial clusters and collected 114 survey responses from CEOs or managers in the three major IT clusters. The empirical results of this study showed that support technologies, management advocacy, and staff expertise had positive effects on absorptive capacity, and absorptive capacity had a positive effect on innovation performance. This study contributes to the understanding of the antecedents and outcomes of absorptive capacity by providing cross-sectional data that presents important theoretical and practical implications.

Least Square method is widely adopted in stereo matching owing to it high precision, but the fact that transformation parameters is obtained by solving linear equations leads to the instability of its solutions and the process of matching oscillates and decreases convergence speed. To overcome this disadvantage, improve convergence speed and keep high precision, this paper provides gradient method to resolve stereo matching. The experiments show that the algorithm is valid and practical.

In this paper, HMM based non-contact gesture recognition using EPS(Electric Potential Sensor) is implemented, First, EMI(Electro-Magnetic Interference) in ELF (Extremely Low Frequency) band from surrounding environments is minimized through EMI removing process as well as preprocessing. Hand gesture recognition algorithms applied for smart TV remote control are presented and evaluated. Our proposed cumulative electric potential based “left to right model” is implemented and its performance is compared to that of an ergodic model based directional vectors. Also, we implement the HMM by finding the optimal numbers of states and quantization, and then compare its performance with other typical algorithms.

Congestion in Wireless Sensor Networks (WSN) get worse when there are multiple and random flows of data in which some have superior significance over the others requiring fidelity in terms of packet delivery, QoS, energy efficiency and throughput. In node-level, congestion leads to impairment of packets that obviously reduces the QoS. In this paper, we present a Cluster based congestion control with Rate Adjustment based on Priority (CRAP) protocol, which self-organizes the sensor nodes into clusters. These clusters monitor congestion in a proactive manner within its confined range which exchanges information among them and adjusts the traffic rate when one cluster has high priority flow over the other. This rate adjustment is based on the exchange of traffic rate estimate among the clusters that reduces packet re-transmissions and energy loss. Our simulation expedites system wide rate control resulting in good throughput, very low packet loss probability and delay that deals with multiple, random flows of data.